# US 11,907,807 B2 · Method and system of enhanced hybrid quantum-classical computing mechanism for solving optimization problems > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,907,807 B2 - Document ID: US11907807B2 - Status: Granted - Kind: B2 - Application number: 17/706,215 - Filed: 2022-03-28 - Published: 2023-09-14 - Granted: 2024-02-20 - Earliest claimed: 2022-03-09 - Assignees: Infosys Limited - Applicants: Infosys Limited - Inventors: Vipul Jain; Aditya Bothra; Vijayaraghavan Varadharajan; Umberto Borso - Web page: https://patentgrep.com/patent/US11907807B2 ## CPC - G06N 10/40: Physical realisations or architectures of quantum processors or components for manipulating qubits, e.g. qubit coupling or qubit control - G06N 10/60: Quantum algorithms, e.g. based on quantum optimisation, quantum Fourier or Hadamard transforms - G06N 3/126: Evolutionary algorithms, e.g. genetic algorithms or genetic programming - G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) - G06Q 30/0244: {Optimization} - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract A method of enhanced hybrid quantum-classical computing mechanism for solving optimization problems is disclosed comprising altering a value of a configuration chromosome by storing an angle memory on a shared classical memory. The angle memory corresponds to a predefined configuration chromosome. The method then generates a state vector based on the angle memory and reinitializes a quantum circuit from the state vector. Subsequently, generating at least two most probable configuration chromosome from the reinitialized quantum circuit corresponding to a superposition of qubits in a position chromosome. Subsequently selecting one of the at least two most probable configuration chromosomes for each position chromosome after evaluation by a fitness function. ## Claims ### Claim 1 An enhanced hybrid quantum-classical computing mechanism for solving optimization problems, comprising; at least one quantum processor unit (QPU); a shared classical memory, the shared classical memory being connected to the at least one QPU; the QPU being configured to alter a value of a configuration chromosome by storing an angle memory on the shared classical memory, wherein the angle memory corresponds to a predefined configuration chromosome; generating a state vector based on the angle memory; reinitializing a quantum circuit from the state vector; generating at least two most probable configuration chromosome from the reinitialized quantum circuit corresponding to a superposition of qubits in a position chromosome; selecting one of the at least two most probable configuration chromosomes for each position chromosome after evaluation by a fitness function. ### Claim 2 (depends on 1) The system of claim 1, wherein the angle memory is configured to store a value of θ in classical memory for each qubit of each configuration chromosome. ### Claim 3 (depends on 1) The system of claim 1, wherein at least one amplitude of the qubits in the configuration chromosome is limited to a set of real values based on the value of θ. ### Claim 4 (depends on 1) The system of claim 1, wherein, a mapping of a chromosome to the qubits of quantum computer is performed through superposition of qubits corresponding to a combination of at least one configuration chromosome and at least one position chromosome. ### Claim 5 (depends on 1) The system of claim 1, wherein, a set of chromosomes are selected based on an evaluation at each generation. ### Claim 6 (depends on 1) The system of claim 1, wherein a rotation operation is performed to select the best chromosome to approximate the state of chromosomes to the state of the optimum chromosome comprising; rotating a set of states of the qubit in the configuration chromosome towards the state of the qubit in the best configuration chromosome based on the modification of the stored value of θ in angle memory. ### Claim 7 (depends on 1) The system of claim 1, wherein a new population of chromosome is generated based on the state vector and the modified value of θ. ### Claim 8 (depends on 1) The system of claim 1 wherein the two most probable configurations are selected from a set of random number of measured configuration chromosomes corresponding to each position chromosome, based upon a probability measure method for a second evaluation using the fitness function. ### Claim 9 A method of enhanced hybrid quantum-classical computing mechanism for solving optimization problems, comprising; altering, through a quantum processor unit (QPU) alter a value of a configuration chromosome by storing an angle memory on a shared classical memory, wherein the angle memory corresponds to a predefined configuration chromosome; generating a state vector based on the angle memory; reinitializing a quantum circuit from the state vector; generating at least two most probable configuration chromosome from the reinitialized quantum circuit corresponding to a superposition of qubits in a position chromosome; selecting one of the at least two most probable configuration chromosomes for each position chromosome after evaluation by a fitness function. ### Claim 10 (depends on 9) The method of claim 9, wherein the angle memory is configured to store a value of θ in classical memory for each qubit of each configuration chromosome. ### Claim 11 (depends on 9) The method of claim 9, wherein at least one amplitude of the qubits in the configuration chromosome is limited to a set of real values based on the value of θ. ### Claim 12 (depends on 9) The method of claim 9, wherein, a mapping of a chromosome to the qubits of quantum computer is performed through superposition of qubits corresponding to a combination of at least one configuration chromosome and at least one position chromosome. ### Claim 13 (depends on 9) The method of claim 9, wherein, a set of chromosomes are selected based on an evaluation at each generation. ### Claim 14 (depends on 9) The method of claim 9, wherein a rotation operation is performed to select the best chromosome to approximate the state of chromosomes to the state of the optimum chromosome comprising; rotating a set of states of the qubit in the configuration chromosome towards the state of the qubit in the best configuration chromosome based on the modification of the stored value of θ in angle memory. ### Claim 15 (depends on 9) The method of claim 9, wherein a new population of chromosome is generated based on the state vector and the modified value of θ. ### Claim 16 (depends on 9) The method of claim 9, wherein the two most probable configurations are selected from a set of random number of measured configuration chromosomes corresponding to each position chromosome, based upon a probability measure method for a second evaluation using the fitness function. ### Claim 17 A computer program product of enhanced hybrid quantum-classical computing mechanism for solving optimization problems, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions are executable by a processor to cause the processor to: alter, through a quantum processor unit (QPU) alter a value of a configuration chromosome by storing an angle memory on a shared classical memory, wherein the angle memory corresponds to a predefined configuration chromosome; generate a state vector based on the angle memory; reinitialize a quantum circuit from the state vector; generate at least two most probable configuration chromosome from the reinitialized quantum circuit corresponding to a superposition of qubits in a position chromosome; select one of the at least two most probable configuration chromosomes for each position chromosome after evaluation by a fitness function.